Opportunities and Challenges in Developing COVID-19 Simulation Models: Lessons from Six Funded Projects

Philippe J. Giabbanelli, Jennifer Badham, Brian Castellani, Hamdi Kavak, Vijay Mago, Ashkan Negahban, Samarth Swarup

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The COVID-19 pandemic showed us the importance of modeling and forecasting efforts to guide decision makers. However, a year into the COVID-19 pandemic, the computational science literature lacks a proper internal exploration of the modeling journey of researchers around the world, including how they responded to the shared challenges our community faced such as data limitations, model fitting and working with public stakeholders. The current paper is a detailed examination of the internal processes of six research teams, which were funded in several countries to model COVID-19. Each team was asked to reflect on the research question and how they solved their respective modeling challenges, as well as how, looking back, they would do things differently.

Original languageEnglish (US)
Title of host publicationProceedings of the 2021 Annual Modeling and Simulation Conference, ANNSIM 2021
EditorsCristina Ruiz Martin, Maria Julia Blas, Alonso Inostrosa Psijas
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781565553750
DOIs
StatePublished - Jul 19 2021
Event2021 Annual Modeling and Simulation Conference, ANNSIM 2021 - Virtual, Fairfax, United States
Duration: Jul 19 2021Jul 22 2021

Publication series

NameProceedings of the 2021 Annual Modeling and Simulation Conference, ANNSIM 2021

Conference

Conference2021 Annual Modeling and Simulation Conference, ANNSIM 2021
Country/TerritoryUnited States
CityVirtual, Fairfax
Period7/19/217/22/21

All Science Journal Classification (ASJC) codes

  • Health(social science)
  • Hardware and Architecture
  • Engineering (miscellaneous)
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

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